The overall objective of this proposed R21 application is to conduct a secondary data analysis of the largest and most comprehensive population study (PINE Study) of US Chinese older adults to identify differential clusters of aging immigrants in terms of family relation patterns and to identify family relation pattern that is associated with favorable mental health outcomes. More specifically, using latent class analysis, a statistical tool that holds great potential, yet rarely used in family studies or among immigrant populations, this proposal addresses three specific aims: 1) Identify different patterns (latent classes) of family relations based on a combination of structural, associational, functional, affectional, and normative solidary; 2) Examine acculturation factors (length of residence in the US, age at migration, reasons for migration, levels of acculturation) that predict each pattern of family relations identified in Aim 1; 3) Identify family relation pattern that is associated with favorable mental health outcomes (i.e., depression, anxiety, loneliness, stress, and quality of life) of older adults. Chinese is a rapidly growing but under-studied minority subpopulation in the U.S. with relatively high rates of mental health problems. As most aging immigrants, the well-being of Chinese older adults is intrinsically linked with their families due to cultural preferences, economic constraints, linguistic isolation, and limited access to formal services. Older immigrants and their families function in a fluid social environment. Family relations are reshaped in the acculturation process, resulting in divergent family experiences even within the same ethnic group. Our knowledge regarding such heterogeneities among older immigrants and their implications for mental health is essentially lacking. This marked research gap is further exacerbated by small, non-probability samples that have been used in most existing studies, as well as the use of a single- dimensional approach that focuses on discrete dimensions of family relations without considering underlying structures that may have shaped different dimensions. To address these gaps, we will use the two-wave panel data of the PINE (N > 2,700) to identify clusters of older adults who are at higher mental health risks by using a novel statistical model approach that provides a unified, comprehensive assessment of the multidimensional family relations, and by identifying the predictors of different family relation types, and the most ?optimal? family relation type that benefits mental health in the long run. The findings from this proposal will inform researchers, clinicians, social service providers, and policy makers to a) better identify at-risk older immigrants for targeted and tailored assessment and interventions, b) better understand the nature of ethnic aging and hard-to-measure family processes among older immigrants, c) develop new ways of research/practice to enhance successful aging of rapidly increasing immigrant populations through a refined family lens.